English learners (ELs) in U.S. schools vary in many ways, in their home languages and the cultures they represent, their proficiency in their home language, the age at which they enter school and their prior schooling in other contexts, and their language abilities and prior knowledge about science, technology, engineering, and mathematics (STEM) subjects. The variability within the EL population was articulated by the National Academies of Sciences, Engineering, and Medicine report Promoting the Educational Success of Children and Youth Learning English: Promising Futures (hereafter referred to as Promising Futures) (NASEM, 2017):

ELs vary in their home language, language abilities, age, race/ethnicity, immigration circumstances, generational status in the United States, geographic distribution, academic achievement, parental characteristics and socioeconomic resources, disability status, and other demographic attributes (Capps, 2015; Fry, 2007). Thus, while on average, ELs have a number of unique characteristics that distinguish them from the general population of non-ELs (Capps, 2015; Fry, 2007), broad comparisons of ELs with non-ELs mask significant heterogeneity within both groups. (pp. 63–64)

Of greatest importance, in relation to placement for STEM learning, is their prior knowledge about STEM subjects, but children are not typically assessed for their content knowledge when entering U.S. schools. Instead, their identification and course placement, at least at the secondary level, is typically determined by their level of English proficiency. As this report

further describes in this chapter and throughout the report, the English proficiency of any person is multifaceted. ELs typically have varying levels of proficiency, both across modes of language use (reading, writing, speaking, listening) and across domains of knowledge, according to opportunities they have had to learn and use language. In addition, the experiences of ELs entering U.S. schools in kindergarten are different from those of ELs entering U.S. schools in late elementary through high school, as older children have greater levels of cognitive development and may have formal knowledge of STEM subjects developed in other contexts. Additionally, some older students may not be orally proficient in English, but may have English reading and writing skills based on prior educational experiences in English in their home countries, which facilitates their pathway to English proficiency and STEM learning in English. On the other hand, some ELs may come to U.S. schools in the secondary years without knowledge of English. They may also have experienced interrupted schooling or significant trauma that prevented them from developing literacy in their primary language or formal knowledge in STEM subjects. This report outlines ways that STEM programs can be designed to offer access to STEM learning opportunities for this range of ELs.

Below we discuss key issues that currently shape the extent to which STEM learning opportunities are accessible to ELs, including (1) the heterogeneity of ELs; (2) the program models through which ELs gain access to STEM subjects; (3) the processes of classification and reclassification of ELs that shape their access to STEM learning; (4) the academic achievement gap; and (5) the particular issues that affect placement of ELs in STEM courses at the secondary level.1

ELs constitute a sizable and fast-growing segment of the student population in the United States. In 2002–2003, 8.7 percent of the enrollment in public schools—about 4.1 million students—was classified as ELs (Kena et al., 2015); in 2014–2015, this percentage rose to 9.4 percent—about 4.6 million students (McFarland et al., 2017). Whereas eight states have EL enrollments of 10 percent of students or more in their public schools, EL enrollment is also growing in most states. For example, the number of states with 6 to 10 percent of students classified as ELs increased from 14 in 2010–2011 (Kena et al., 2015) to 18 in 2014–2015 (McFarland et al., 2017). While in 2013, there was a growth of 7 percent in the general student population over 10

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1 This chapter includes content from a paper commissioned by the committee titled K–12 English Learners’ Science and Math Education: A Question of Curricular Equity (Callahan, 2018).

BOX 2-1 Unpacking the Complexity of the Heterogeneity of English Learner (EL) Students

Effectively addressing heterogeneity is critical to properly supporting ELs to have access to STEM subjects through placement, instruction, and assessment. This heterogeneity has two facets. The first concerns the wide linguistic diversity and complex geographical distribution of ELs. There are nearly 5 million students classified as ELs in K–12 public schools (and many others who have gained proficiency in English)—about 10 percent of the student enrollment (U.S. Department of Education, 2018). Altogether, these students are native users of a total of 150 languages. The most common is Spanish (more than 77%), followed far behind by Arabic (2.4%), Chinese (2.1%), Vietnamese (1.7%), and other languages spoken by less than one-tenth of 1 percent of ELs each. However, there are seven states (Alaska, Hawaii, Maine, Montana, North Dakota, South Dakota, and Vermont) in which the most frequently native language among ELs is a language other than Spanish (Batalova and McHugh, 2010). Although about two-thirds of the total enrollment of ELs in the country is concentrated in eight states (California, Colorado, Florida, Illinois, New York, North Carolina, Texas, and Washington), there are states with high and rapidly increasing percentages of ELs, as is the case of Nevada, with 17 percent of its students classified as ELs (Ruiz-Soto, Hooker, and Batalova, 2015). Due to this heterogeneity, each state has a unique set of challenges to overcome to properly support EL students.

The second aspect of heterogeneity concerns the fact that English proficiency has multiple forms and is shaped by cultural experience. Against common intuition, the majority of ELs in the country are U.S. born (Zong and Batalova, 2015). Their diversity originates not only from their multiple cultural heritages, but also from their wide variety of schooling histories and, therefore, the different kinds of support they have received to both develop English as a second language and to continue developing their first language. As a result of this variety, each EL student has a unique set of linguistic skills. For example, two ELs who are in the same classroom and are native users of the same language may differ considerably in their skills across the four language modalities (listening, speaking, reading, and writing) in each of their two languages. Even if both are fluent in conversation in their first language, their reading and writing skills in the first language may vary considerably if one has a history of instruction in that language and the other does not. Clearly, broad categories of English proficiency do not provide the kind of information on English proficiency that is needed to make sound decisions for ELs.

Legislation, policies, programs, and instructional and assessment strategies are limited in their effectiveness to serve ELs when this tremendous heterogeneity is not recognized. For example, testing all ELs in their first language could be more harmful than beneficial for those who have received limited formal instruction (and, therefore, have developed limited reading and writing skills) in that language (Solano-Flores and Hakuta, 2017). Particularly concerning is the fact that this failure to address heterogeneity may lead educators and schools to overestimate proficiency in the first language and to underestimate English proficiency.

Decisions concerning instruction and assessment need to be made based on recognizing the tremendous heterogeneity of EL populations if their access to STEM content is to be effectively supported. Proper strategies in instruction and assessment include (1) making decisions based on detailed information on proficiency in the four language modalities of English, beyond the simple use of broad classification categories; (2) using multiple sources of information (in addition to scores on English proficiency tests) in judging students’ English proficiency; (3) looking for approaches that are sensitive to each student’s needs; (4) avoiding making assumptions about the proficiency of students in English or in their native language; and (5) encouraging educators to develop a good sense of each of their ELs’ strengths in English, based on continuously interacting with them.

Long-Term ELs

The majority of the U.S. EL population across all ages between 5 and 17 is born in the United States and typically has at least one immigrant parent; however, in the secondary grades there are almost equivalent levels of U.S.-born and foreign-born ELs as compared to elementary settings that are predominantly U.S. born (NASEM, 2017, pp. 73–74). Often referred to as “long-term ELs” or “LTELs,” many of these students have been receiving English language development/English as a second language (ELD/ESL) services in U.S. schools for at least 6 years and yet have not met reclassification criteria for their state (Batalova, Fix, and Murray, 2007; Menken and Kleyn, 2010; Solis and Bunch, 2016). This group has attracted increased attention as they represent a sizable portion of the EL population (Menken, 2013). Some states are beginning to provide a designation for these students; however, there may not be consistency across states in defining this particular subpopulation of ELs (Olsen, 2010). The lack of a consistent definition makes it difficult to interpret and draw conclusions with respect to how these students are performing in STEM subjects.

The research has shown that there is a plateauing of English proficiency for LTELs from middle to high school and that this may be related to the academic tracking of ELs that occurs in these grades (NASEM, 2017). Although the intention of tracking may be to advance LTELs to be classified as English proficient, they are often assigned to low-level academic classes (described in more detail later). The continued placement of these students in ESL courses, as this chapter will detail, often prevents them from accessing STEM education and the opportunities STEM offers for language development (Callahan, Wilkinson, and Muller, 2010).

Newcomers

Few studies provide research evidence related to newcomers, those foreign-born ELs and their families who have recently arrived in the United States (U.S. Department of Education, 2016). Heterogeneity within this group of students compares to the heterogeneity within the U.S.-born EL population and is driven by many of the same factors, as well as factors unique to this subgroup. These students may have experienced interrupted or limited formal education and often exhibit low levels of English language proficiency and academic achievement compared with their peers (NASEM, 2017). The initial difficulties newcomers experience may be linked to having to adjust to a new language and culture while developing literacy as well as oral and academic proficiency in English in a relatively brief period of time (Menken, 2013). Newcomers often receive specialized ESL instruction that socializes them into the new school practices they encounter and provides opportunities for language development calibrated to their newcomer status. However, even newcomers can interact with children who speak English and participate and contribute in authentic STEM learning contexts. As newcomers begin to use language to learn and interact socially, their interaction with peers and adults in authentic learning contexts leads to continued control of English (Solano-Flores, 2008).

Linguistic Heterogeneity

If teachers get information about the ELs in their classrooms, the students’ English proficiency may be reported at particular levels of proficiency in listening, reading (language comprehension), speaking, and writing (language production), or they may receive an overall proficiency level. However, research has suggested that formal, largely summative, large-scale language assessments may be a problematic way to measure language proficiency (Cumming, 2008; Valdés, Capitelli, and Alvarez, 2011; Valdés, Poza, and Brooks, 2014; see Box 2-2), missing much of the communicative aspects of authentic classroom interaction during instruction (Bailey

and Durán, in press). ELs vary in their control of these different skills and this can interact with their prior schooling (Solano-Flores, 2008). Box 2-2 illustrates the ways in which ELs can vary along the various dimensions of English proficiency measured. Given this variability in the EL population, it is important for educators to find out what learners know about STEM subjects from their previous schooling and experiences, and to connect with and build on prior learning in their first languages. As stated in previous reports, ELs can develop fluency in language and the language of STEM subjects over several years of engagement and participation in grade-appropriate activities (NASEM, 2017).

Although the process of language learning is similar for all students, ELs experience different overall trajectories in their learning of language and STEM content related to their ages and levels of English proficiency, prior knowledge, and community context (Solano-Flores, 2008). As described above, older children who can read and write in their first language may

BOX 2-2 Using Linguagrams to Understand the Heterogeneity of English Learners (ELs) in the Classroom

Linguagrams are conceptual tools created with the intent to support teachers to reason about the linguistic heterogeneity of EL students in their classrooms (Solano-Flores, 2016). A linguagram consists of a symmetric bar graph that represents an individual’s proficiency in English and in their first language in each of the four language modalities—listening, speaking, reading, and writing—on a scale that ranges from 0 (total lack of proficiency) to 100 (full proficiency).

The figure below shows the linguagrams of three hypothetical EL students who are in the same classroom and are native speakers of the same language. Different personal experiences (e.g., family, community, friends) and different schooling histories produce different sets of opportunities to become proficient in listening (L), speaking (S), reading (R), and writing (W) in each language. The three cases shown are among the many possible combinations of levels of proficiency that different ELs may have in their two languages.

To reason about the linguistic diversity in their classrooms, teachers can be asked to construct linguagrams of each of their EL students using information from multiple sources, in addition to test scores. Examples of these sources are observations of the students interacting with other ELs or with never-EL students, teachers’ informal interactions with the students, students’ participation in class, examination of students’ written work, and conversations with the students’ parents (e.g., to know the students’ schooling history).

Linguagrams are not a formal assessment instrument, but a tool to support

have an advantage over younger children who have yet to develop literacy in any language. Younger children may need additional support when learning language and STEM content (see Chapter 4). With respect to community context, children who live in more linguistically homogeneous communities are well positioned to draw on their first-language proficiency as an asset in STEM learning, making bilingual education and/or strategic use of the first language in the classroom an important part of their learning contexts. For ELs who live in more linguistically diverse communities, attention to and participation in a range of oral and written languages and registers at school (see Chapter 3) can be a part of their STEM learning experiences (for review, see U.S. Department of Education, 2012). For all ELs, opportunities to participate in authentic STEM practices, with attention to language use in meaningful ways, are crucial to enabling these learners to bring their full range of knowledge and resources to learning and to realize their full potential as STEM learners (see Chapter 4).

teachers to realize that (1) little information is typically available about their EL students’ proficiency in English or in their first language; (2) although useful, information from tests of language proficiency does not have the level of detail needed to know exactly how to support ELs in the classroom; (3) a great deal of the information needed to develop a good sense of the linguistic proficiency of ELs needs to be obtained through socially interacting with them; (4) each EL has a unique pattern of language dominance; and (5) language proficiency varies considerably across contexts (e.g., in class, during a mathematics conversation, or in informal situations).

Federal legislation over the past 20 years has called for English instruction for ELs that enables them to succeed in learning across school subjects. The No Child Left Behind (NCLB) Act of 2001 mandated that states “establish standards and objectives for raising the level of English proficiency . . . that are aligned [emphasis added] with achievement of the challenging State academic content and student academic achievement standards” (U.S. Department of Education, 2001, pp. 270–271). Even though the U.S. Department of Education has allowed flexibility on federal accountability provisions, it has still required that each state “adopt English language proficiency (ELP) standards that correspond [emphasis added] to its college- and career-ready standards” (U.S. Department of Education, 2012, p. 1). Although subsequent legislation has used slightly different terminology, the mandate has remained the same: ELP standards must describe how ELs will use language to master content. This series of federal legislation communicates a clear message that the aims of content learning and language learning are closely tied to each other and are best addressed in parallel or in conjunction, rather than separately or sequentially (Lee, 2018). In other words, ELP is not a prerequisite for ELs’ inclusion in content instruction.

Prior to 2000, much of the research on ELs was focused on the language of instruction—the use of primary language in instruction (Francis, Lesaux, and August, 2006): that is, that research was preoccupied with the question of which language to use when instructing non-native speakers of the societal language. Although current research focuses more closely on the language in instruction, regardless of whether that language is the home language or English, the language models under which a student has learned represent an important dimension of the heterogeneity of schooling experiences. In other words, whereas current research focuses more on the quality of the language used in instruction than on the choice of whether to deliver instruction in the children’s home language or the societal language, this choice of the language of instruction marks an important dimension along with ELs educational experiences differ. Moreover, the variety of program models and variability in the quality of instruction under all program models complicates the process of drawing inferences from the literature on effective practices.

Program models can first be distinguished by their use of students’ primary language in instruction. Table 2-1 highlights several types of primary language development programs, summarizing each program and illustrating many of the key features (NASEM, 2017). These programs, whether it be an ESL or bilingual program model, differ in their emphasis on the primary language. For example, in transitional programs (see TBE in table), the primary language is viewed as a bridge to support instruc-

tion until students can function independently in English-only instruction. Transitional programs differ from one another not only in the timing of the transition to English but also in the extent to which primary language is used in content and literacy instruction. Developmental bilingual programs and maintenance programs view primary language as a cognitive resource to develop and/or maintain throughout the child’s time in the program. This development typically occurs in literacy instruction and occasionally in content area instruction. Dual-language programs (see Two-Way Dual Language Immersion in table) differ in that by design they include never-ELs who seek to become proficient in a language other than English (U.S. Department of Education, 2012). This type of program offers content instruction in all subject areas in and across both languages of instruction.

Program labels mask the heterogeneity in instructional settings, in the extent of English and primary language in instruction, the areas of instruction in which the two languages might be used, and the quality of the instruction. Moreover, program labels imply an approach to instruction that may not extend to content area instruction. One cannot assume that bilingual instruction extends to instruction in STEM, nor can one assume that ELs are receiving STEM instruction, regardless of the program label. These circumstances mean that ELs may have little access to grade-appropriate STEM content and will continue to fall behind in their STEM development as the challenges of STEM learning increase at every grade level.

These trends have historical roots in federal policy. For example, the Bilingual Education Act of 1968 framed bilingual instruction as a means to English proficiency rather than as support for continued subject area learning as students learn English (Evans and Hornberger, 2005; Ruiz, 1984). Given that the underlying goal of this policy was to move students to English-only instruction as quickly as possible, bilingual programs have not always provided support for ELs’ continued development of grade-level content knowledge (García, 2009; Ramírez et al., 1991). Even when bilingual programs are offered, the provision of primary language support for STEM learning is uneven, as some programs are designed such that students engage in language arts instruction in their primary language, but mathematics and science instruction is offered only in English (Boals, 2001). It is important to note that research on program models has tended to focus on student performance in reading and mathematics and has concentrated in the elementary grades, suggesting a need for further research. This focus is not surprising given that federal policy has not legislated assessment of student outcomes in science until recently, and even now science is assessed in a limited number of grades in comparison to reading and mathematics. This general lack of focus on STEM outcomes beyond mathematics until recently and these sources of variation that exist even within programs of the same type are important for the reader to keep in mind in the discus-

sions about supporting teachers, structuring classrooms, and setting policies in later chapters. The first of these had led to a paucity of focused research on STEM instruction for ELs whereas the latter complicates the formation of easy generalizations from the research that does exist.

In all programs serving ELs, special attention to their ELD is crucial and required by law. Program models differ in how ELD support is provided. In some settings, ELs are pulled out of general education classrooms to receive ELD support, which precludes them from accessing the content in general education classrooms. As currently operationalized in many U.S. schools, ELD is often not organized in a way that enables ELs to maintain and develop age-appropriate knowledge of STEM subjects (Saunders, Goldenberg, and Marcelletti, 2013). When ELs are integrated into content classes, teachers, both those who teach ELD and those who teach content, are not typically prepared to support ELs’ simultaneous development of language and STEM content knowledge (Bunch, Aguirre, and Téllez, 2009). Classrooms that provide sheltered approaches often provide highly simplified content that seldom satisfies grade-level STEM content expectations (Dabach, 2014; Saunders, Goldenberg, and Marceletti, 2013). Later chapters in this report will describe how such support for ELs can be provided in STEM classrooms and how ELD and STEM can be integrated.

Moreover, continuing to develop ELs’ content knowledge through bilingual support clearly shapes students’ long-term academic trajectories (Steele et al., 2017; Valentino and Reardon, 2015). In a lottery study using seven cohorts of students who applied at a PreK or kindergarten immersion program, Steele et al. (2017) found that there was a 6 percentage point reduction in the probability of being classified as an EL in 5th grade and a 14 point reduction in 6th grade; however, the effects on mathematics and science learning were less evident. Valentino and Reardon (2015) examined four different instructional program models—Transitional Bilingual (TB), English Immersion (EI), Developmental Bilingual (DB), and Dual Immersion (DI)—and ELs’ academic outcomes in English language arts and mathematics. They found that in 2nd grade, mathematics scores of ELs enrolled in all program models were significantly higher than the state average, with those enrolled in DB and TB classrooms even higher, respectively.

However, by 7th grade, the rate of growth was slowest for DB classrooms, about average for EI and DI programs, and those in TB programs were higher than the state average (Valentino and Reardon, 2015). At the same time, Umansky (2016) used a regression discontinuity design to assess the impact of program model by comparing students classified as EL and students with similar language skills who just missed being classified as EL. Umansky (2016) found a negative effect of EL classification on content area outcomes where students were enrolled in EI programs that was not present for students enrolled in bilingual instruction. Regardless of any conclusions about specific program models, what is clear from this research is that, even very early on, the language of instruction shapes ELs’ content area access and academic trajectories.

The advantages of bilingual and primary language instruction identified above are not automatically obtained, nor are bilingual programs the norm in the United States. Whereas quality bilingual instructional programs could be more widespread than they are, the diversity of languages spoken by U.S. school children, the dearth of qualified bilingual educators, and the sparse representation of some languages in some locales (McFarland et al., 2017) make instruction in the primary language not always feasible. These factors necessitate that all schools be prepared to provide high-quality instruction to ELs, regardless of the choice of language program model within that school, including the implementation of effective programs within that school.

The classification of students as EL is complex and varies considerably across states, and even across districts within states (Cimpian, Thompson, and Makowski, 2017). Initial EL classification is determined by a student’s level of ELP as demonstrated by standardized assessment results (discussed in more detail in Chapters 7 and 8). Although in many states, the state ELP assessment is the sole criterion for classification and reclassification as English proficient, or a student’s readiness to exit EL status and related programs and services, other criteria include (1) academic achievement measured by standardized test scores and/or grades in English language arts and/or mathematics, (2) teacher evaluation, and (3) in some cases, parent consultation and/or approval. The inclusion of the second indicator, which requires that ELs perform at grade level in school subjects before being reclassified, varies across states and districts within states, and is used in some states with large EL populations. While including proficiency in content achievement as a criterion for language proficiency appears reasonable, the fact that many students who are non-ELs are not proficient in content achievement raises questions about content achievement as a

criterion for English proficiency. Most importantly, tying reclassification to content achievement often delays reclassification and precludes ELs from being enrolled in STEM courses. In this sense, EL status penalizes students by preventing them from having access to academically rigorous curricula, in spite of research indicating that access to academic content is associated with ELs’ achievement, as it is for non-ELs (Oakes, 2005). Moreover, given that students continuously enter and exit EL status (Hopkins et al., 2013), it is challenging to develop complete understandings of how ELs fare in schools and classrooms, and the extent to which both ELs and reclassified ELs have access to rigorous STEM content.

Reclassification is a challenging issue, as both too-early reclassification and too-late reclassification have negative outcomes for ELs (Robinson-Cimpian, Thompson, and Umansky, 2016). Slama’s (2014) longitudinal analyses found that ELs who were reclassified early in elementary school (Grades K–2) struggled later on, with nearly one-quarter being retained a year. Slama and colleagues (2015) illustrated how early reclassification among ELs in English-only contexts is not only associated with retention, but also with attrition from the K–12 education system entirely. For ELs, as for all young children, language development continues in the early elementary grades as they continue developing literacy skills, so ensuring that EL supports are reduced at the appropriate time is an important issue. Although early reclassification may appear to indicate success, long-term consequences with respect to retention and attrition matter more in the long run (Thompson, 2015b). Most ELs continue to benefit from language support even after they demonstrate conversational fluency and ability to participate fully with the curriculum in the earliest grades (Saunders, Goldenberg, and Marceletti, 2013).

On the other hand, keeping ELs in specialized language programs can prevent them from having access to STEM learning opportunities. Reclassification by the end of the elementary grades, for example, is important for facilitating ELs’ access to advanced STEM courses in high school. In a longitudinal analysis of student-level data from the Los Angeles Unified School District, the largest EL-enrolling school district in the nation, Thompson (2017a) found that the vast majority of ELs demonstrated English language proficiency within 4–7 years. However, her analyses also indicated that if a student missed the late elementary reclassification window, the likelihood of ever reclassifying dropped significantly. In fact, a full 25 percent of ELs remained classified after 9 years in the school system (Thompson, 2017a).

Thompson (2015b) also showed how missing the reclassification window can result in long-term EL status and continued placement in ELisolated programs that provide limited access to grade-level curriculum. Specifically, Thompson (2017b) showed how external, organizational constraints prevent long-term EL students from advancing in mathemat-

ics. However, barriers to EL students extend beyond access to courses. Callahan and Humphries (2016) further showed how EL students experience lower returns on advanced mathematics course-taking relative to both other immigrants and native-born, native-English speakers. Even when EL students manage to complete honors-level advanced mathematics, calculus or beyond, they fail to receive the same boost in 4-year college-going experienced by all other student groups. These effects are present even after controlling for student performance in advanced mathematics courses. Accuracy in reclassification is especially important because the retention of students in EL status longer than necessary also results in stigmatizing, negative educational experiences (Estrada and Wang, 2013; Thompson, 2015a) and can be academically and linguistically detrimental to students (Calderón and Minaya-Rowe, 2011; Menken and Kleyn, 2009; Olsen, 2010). In a recent qualitative case study of three students who were labeled long-term ELs, Thompson (2015a) demonstrated the stigmatizing, limiting aura associated with this status, as well as how the students experience its accompanying constraints to their academic identities. Often, long-term ELs internalize the negative social and academic perceptions that have come to characterize EL-focused courses and programs (Dabach, 2015). These negative perceptions are fueled in part by the inaccurate reporting of student achievement among students who enter school as ELs that results from the routine exclusion of reclassified ELs when reporting on EL achievement (Saunders and Marcelletti, 2013).

The EL subgroup is unlike other accountability subgroups under Title I in that the EL designation is dynamic—a student’s classification as EL changes as the student becomes proficient in English. Importantly, as children become proficient in English, they are reclassified and no longer count in the category of EL. This dynamism in EL classification leads to overestimation of achievement gaps between ELs and never-ELs (Saunders and Marcalletti, 2013), overestimation of ELs in special education (Umansky, Thompson, and Diaz, 2017), and underestimation of EL graduation rates (Thompson et al., 2017). In fact, Saunders and Marcalletti (2013) have termed the achievement gap “The Gap That Can’t Go Away,” because as ELs gain proficiency in English, they are also increasingly likely to demonstrate proficiency in content area achievement, but are now counted among the non-EL category for accountability purposes, creating an achievement gap that must persist.

The best indicators of this achievement gap are provided by the National Assessment of Educational Progress (NAEP)—a national assess-

ment that has been administered to representative samples of students at Grades 4, 8, and 12 from all states since 1969. The performance of ELs on this assessment has been substantially lower than that of their non-EL counterparts. This trend has not changed substantially since 1996, when NAEP started collecting data for ELs. According to data from 2015, the mathematics performance of ELs was, on average, 25 points lower than that of non-ELs at Grade 4—a gap that is not different from the gap observed in 1996. For Grade 8, while the gap narrowed from 46 points in 1996 to 41 points in 2013, and to 38 points in 2015, these data show a clear increase in the mathematics achievement gap with grade level. For Grade 12, in 2015, the gap was also 38 points different, but the percentage of students “below basic” was higher for ELs than non-ELs than in Grade 8 (for both mathematics and science) (McFarland et al., 2017).

These trends indicate an increase in the achievement gap between EL and non-ELs as they progress across grades in school. However, as described above, this difference could be exacerbated by the exclusion of English-proficient ELs from the EL group. A recent analysis by Kieffer and Thompson (2018) attempted to address this issue. They found that the mathematics performance of students designated as multilingual (defined as the primary home language or languages other than English) was improved as compared to current ELs (defined as those not yet proficient in English in the year of assessment). Including potentially English-proficient ELs in the EL (multilingual) group showed a reduction in the achievement gap. Given these confounding factors, it is difficult to make simple interpretations of the change in the magnitude of the EL—non-EL academic achievement gap between Grades 4 and 8.

Bailey, Maher, and Wilkinson (2018) also reported increases in the achievement gap with grade level for NAEP science assessment scores, and even larger discrepancies between EL and non-ELs than those reported for mathematics: The science performance of ELs in 2015, on average, was 37 points lower than that of non-ELs at Grade 4 and 47 points lower at Grades 8 and 12. Consistent with these trends, data from a longitudinal study with ELs grouped according to different levels of English proficiency at the time they entered kindergarten show that, at Grade 8, reading, mathematics, and science scale scores decline as the level of English proficiency declines (Mulligan, Halle, and Kinukawa, 2012).

Not surprisingly, these trends are reflected in high dropout rates among ELs. About 90 percent of native English users between the ages of 18 and 24 years who are not enrolled in high school have completed high school or earned a GED (Callahan, 2013). In contrast, only 69 percent of ELs within the same age not enrolled in high school have completed high school or earned a GED. In general, at Grade 10, ELs are twice as likely as their never-EL peers to drop out (Callahan, 2013).

Several important factors may contribute to these achievement gaps, although their influence is subject to debate. On one hand, the most important and obvious set of factors concern the intrinsic challenges that stem from learning and being assessed in a second language and from developing academic language (see Schleppegrell, 2004). Whereas experts question the soundness of assessing students in a language that they are still developing (Hakuta, Butler, and Witt, 2000; Moore and Redd, 2002), this notion is not reflected in assessment legislation and policy, which persistently appear to be driven by the implicit assumption that a few years of schooling in English paves the way for ELs to meet the linguistic demands inherent to benefitting from instruction. On the other hand, based on the notion that “what gets measured gets done,” some argue that including ELs and other minority subgroups in large-scale assessment programs is a way of ensuring that these groups are properly served, as there is no evidence that ELs’ educational outcomes were better when ELs were excluded from assessment and accountability (Abedi, 2010).

There is consensus among specialists that linguistic demands in both science and mathematics content can be substantial, and learning in these content areas is associated in part with meeting these linguistic expectations and discourse practices (for science, see Snow, 2010). In the case of mathematics, these understandings run counter to prior assumptions that mathematics learning did not rely heavily on linguistic demands. These linguistic demands concern not only vocabulary, but also discursive forms, ways of constructing arguments, and sophisticated conventions of socialization through language. From a broader perspective, learning science and mathematics entails learning to interpret and to represent knowledge through multiple semiotic modalities (e.g., textual, symbolic, and visual forms of representation) according to conventions that are mediated by cultural experience (Avalos, Medina, and Secada, 2018; Lemke, 1998). These multimodal representations may help to mitigate some of the linguistic demands. This notion holds not only for content learned or taught, but also for the tests that assess that content, as test items have formatting and linguistic features not frequent in other forms of text and may be unfamiliar to many ELs (Bailey and Butler, 2004; Solano-Flores, 2016).

A second set of factors concerns the effectiveness of the support ELs receive. There is a serious lack of educators with formal training in the teaching of ELs (Darling-Hammond and Berry, 2006; Santos, Darling-Hammond, and Cheuk, 2012) and the resource educators who may be in charge of supporting ELs may not have the formal qualifications needed. In addition, the support received by ELs may emphasize English skills over academic content (see Chapter 4 for more information).

A third set of factors concerns social disadvantage, which is reflected by indicators such as household income, parents’ education, and opportunity

to learn. Compared to their never-EL peers, ELs are more likely to live in households with an income below the poverty line. Also, ELs are less likely than their never-EL counterparts to have a parent with a college degree and more likely than their never-EL counterparts to attend low socioeconomic status (SES) schools with poorly qualified or unexperienced teachers (see EPE Research Center, 2009). It is worth noting that high-quality dual language education programs may moderate the effects of SES and poverty (Collier and Thomas, 2017; García, 2009) on EL outcomes as well as capitalizing on the resources that families bring to schools (Yosso, 2005).

It is not reasonable to expect that students perform well on tests on content that they are not taught (see Porter, 2002). Thus, opportunity to learn through exposure to content is especially important in interpreting EL performance. There is evidence of correlation between measures of mathematics achievement and measures of class-level opportunity to learn that comprise indicators such as whether topics are covered in class, the time allocated to cover those topics, the kind of emphasis those topics are given in the curriculum, and the effectiveness with which teachers support students to learn them (Herman, Klein, and Abedi, 2000).

As articulated in the previous section, achievement gaps between ELs and never-ELs increase from elementary school to secondary school (Kena et al., 2016), and ELs are graduating from high school at lower rates than other traditionally underrepresented groups such as never-EL Latino students, African American students, or low-income students. Research across a variety of state contexts has shown that ELs are often systematically excluded from rigorous or advanced coursework in science due to scheduling constraints as well as the misconception that they must be proficient in English before they can be successful in content area classes (Callahan, 2017; Gándara and Hopkins, 2010). This exclusion has had severe consequences on educational opportunities for ELs (Combs, Iddings, and Moll, 2014). ELs fare far better in terms of both content and language measures as well as requirements for graduation and college admissions when they have opportunities to learn rigorous academic content, such as that found in advanced secondary science courses (Callahan, 2005, 2017).

mathematics content, and Algebra II has been identified as a core indicator of preparation for higher education at the national level (Adelman, 2006). In a study using the nationally representative High School Longitudinal Study (HSLS:2009) data, Schneider and Saw (2016) found course-taking to be a stronger predictor of college-going than individual students’ concrete knowledge of college itself, improving the likelihood of college-going for academically marginalized youth.

Yet the availability of rigorous STEM courses varies by school and community. Using the Education Longitudinal Study of 2002 (ELS:2002) data, Riegle-Crumb and Grodsky (2010) found that low-income Latino and African American students enrolled in segregated schools2 struggled the most to reach the highest levels of mathematics course-taking. In an investigation of access to advanced mathematics courses within the context of the New Latino Diaspora,3Dondero and Muller (2012) found evidence of greater Latino-white disparities in mathematics course-taking when taking into account school composition, quality, and resources. Others have found that only one in three students graduate in high EL-density schools (Silver, Saunders, and Zarate, 2008), and that second-generation ELs experience a more concentrated negative estimated effect of ESL placement on their mathematics and science course-taking than their foreign-born peers (Callahan et al., 2009).

More recent data from the HSLS:2009 high school transcript study4 demonstrated students’ course-taking patterns after the onset of the national accountability movement initiated with NCLB. Once again, disparities in course-taking emerge by student linguistic status. The data showed that ELs were overrepresented in lower-level mathematics courses compared to other bilinguals and native English speakers. Initially, twice the share of high school ELs fail to complete any mathematics classes during high school relative to their native English-speaking peers (4.8% compared to 2.4%). And, at the tail of the distribution, fewer than 5 percent of ELs complete advanced mathematics coursework, after calculus, compared to 18 percent of other bilinguals and 10 percent of native English speakers. These disparities in the highest levels of mathematics course-taking remain, even

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2 Segregated schools are defined as schools with a higher share of students from traditionally underrepresented backgrounds: that is, the percentage of the student body that is either African American or Hispanic.

3 The New Latino Diaspora: Research in this area examines the relatively recent (past 20 years) movement of new immigrants and Latinos into the Midwest and the U.S. Southeast. For more information on this topic, see writings on the New Latino Diaspora (Lowenhaupt, 2016).

4 The EL population is defined in the HSLS as EL students who take ESL coursework during high school. In accordance with National Center for Education Statistics restricted use guidelines, all sample sizes are rounded to the nearest 50.

after the implementation of a national accountability movement intended to improve student success.

With respect to science course-taking, the story is more complex; unlike mathematics, science course-taking is neither linear nor hierarchical. Again using the HSLS:2009 dataset, the data indicate that ELs are more likely not to take any science course, and complete higher shares of lower-level, noncollege preparatory sciences (e.g., integrated and earth science) than other bilinguals or native English speakers. In addition, while one-half of ELs (50.4%) complete chemistry, a fairly standard requirement for 4-year college-going, the chemistry completion rates of other bilinguals and native English speakers are nearly 20 percentage points higher (72.4% and 70.4%, respectively). Likewise, while nearly 12 percent of ELs take honors-level science courses during high school, that number is far lower than the 20 percent of native English speakers and nearly 30 percent of other bilinguals who do so.

It is important to keep in mind that the data from these studies merely present descriptive statistics; these analyses do not account for English proficiency, time in U.S. schools, or any of the myriad issues that shape both EL status and students’ overall course-taking. Nonetheless, they point to disparities in ELs’ access to STEM coursework, a trend that has persisted for decades (Hopstock and Stephenson, 2003). For example, Callahan (2005) examined ELs’ English proficiency against their course placement and found that whereas course-taking demonstrated a strong positive association with high school credit completion, overall GPA, and mathematics test scores, students’ level of English proficiency was associated only with reading and language arts test scores.

Even in courses designed specifically to meet ELs’ needs, research shows that they often cover less content, and do so at a slower pace compared to general education classes (Ek, 2009; Estrada and Wang, 2013; Harklau, 1994). Estrada and Wang’s (2013) analyses specifically characterized courses designed for ELs as following a slower pace and engaging students in less depth and rigor of content. Moreover, they showed that the vast majority of ELs who are placed in general education mathematics courses performed poorly and thus had to repeat them. In some cases, these trends in poor performance are related to disparities in curricular resources and access to highly qualified teachers in schools serving ELs (Umansky, 2016). As such, although course-taking is an important marker of EL access to STEM content, research has demonstrated a persistent, negative relationship between EL status and mathematics and science course-taking. Moreover, mere placement in STEM courses does not mean that ELs are afforded equitable access to rigorous STEM content.

Throughout this chapter, many of the factors that have been suggested to impact an understanding of ELs and their access to rigorous STEM content were addressed. ELs come to U.S. schools having varying levels of proficiency, both in their home language and in English, across the modes of language use (listening, speaking, reading, and writing) and having varying prior experience with STEM learning. This heterogeneity is further compounded by heterogeneity in the age at which they enter school, as foreign-born ELs may have no formal school experience prior to arrival in the United States. They may also have experienced interrupted schooling, or significant trauma that prevented school attendance or did not allow for literacy in their primary language to be attained. Added to this heterogeneity in the population, there are a variety of program models used in the United States—ESL or bilingual approaches—that differ in their emphasis on language development and STEM content learning. These approaches have implications for ELs’ acquisition of English proficiency, their reclassification to English-proficient, and can further impact their access to STEM courses and rigorous content. At the same time, these factors simply define the starting point for examining the research to determine how the educational experiences of ELs can be transformed to create more optimal STEM learning for this large, growing, and diverse subset of U.S. students.

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Hopstock, P.J., and Stephenson, T.G. (2003). Descriptive Study of Services to LEP Students and LEP Students with Disabilities: Special Topic Report #1 Native Languages of LEP Students. Washington, DC: U.S. Department of Education, Office of English Language Acquisition.

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Slama, R.B. (2014). Investigating whether and when English learners are reclassified into mainstream classrooms in the United States: A discrete-time survival analysis. American Educational Research Journal, 51(2), 220–252.

Solano-Flores, G. (2008). Who is given tests in what language by whom, when, and where? The need for probabilistic views of language in the testing of English language learners. Educational Researcher, 37(4), 189–199.

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The imperative that all students, including English learners (ELs), achieve high academic standards and have opportunities to participate in science, technology, engineering, and mathematics (STEM) learning has become even more urgent and complex given shifts in science and mathematics standards. As a group, these students are underrepresented in STEM fields in college and in the workforce at a time when the demand for workers and professionals in STEM fields is unmet and increasing. However, English learners bring a wealth of resources to STEM learning, including knowledge and interest in STEM-related content that is born out of their experiences in their homes and communities, home languages, variation in discourse practices, and, in some cases, experiences with schooling in other countries.

English Learners in STEM Subjects: Transforming Classrooms, Schools, and Lives examines the research on ELs’ learning, teaching, and assessment in STEM subjects and provides guidance on how to improve learning outcomes in STEM for these students. This report considers the complex social and academic use of language delineated in the new mathematics and science standards, the diversity of the population of ELs, and the integration of English as a second language instruction with core instructional programs in STEM.

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